Ethical use of artificial intelligence and new technologies in Education 5.0
Open accessAbstract
AI-powered tools such as text-generating algorithms, automatic essay graders, and plagiarism detection software are some of the tools that may be used by the students for improving their skills.For Primary and Secondary Education students, Artificial Intelligence (AI) tools offer a variety of ideas, essay outlines and answers to questions.Generally, students can use AI tools appropriately to improve their learning experience.However, AI tools can be used by students for cheating on assignments and/or exams.It is crucial for a professor or a school generally, to educate students on the ethical use of AI-powered tools and emphasize the importance of academic integrity to prevent cheating.The purpose of this paper is to examine and propose some AI-powered tools that could be used by professors for enhancing students' interaction and engagement.Moreover, the ethical issues for using AI and New Technologies in Primary and Secondary Education will be described using the examples of the proposed AI-tools.Finally, some recommendations and scenarios for responsible use of AI will be suggested in order to be used by policy makers and schools.The findings will be practical and significant, as not enough attention has been paid in Ethical use of AI in Primary and Secondary education.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Lo, C. K. (2023) · Education Sciences · doi:10.3390/educsci13040410 · Cited by 2,024 · see citing works
Artificial intelligence in education: Addressing ethical challenges in K-12 settings
Akgun, S., & Greenhow, C. (2022) · AI and Ethics · doi:10.1007/s43681-021-00096-7 · Cited by 1,473 · see citing works
Ethics of AI in Education: Towards a Community-Wide Framework
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., et al. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00239-1 · Cited by 1,437 · see citing works
Evolution and Revolution in Artificial Intelligence in Education
Roll, I., & Wylie, R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0110-3 · Cited by 1,229 · see citing works
Ethical principles for artificial intelligence in education
Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B.-P. T. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11316-w · Cited by 1,228 · see citing works
British Journal of Educational Technology
Wang, K., Qin, S., Shen, Y., Guo, J., Ruan, Q., & Jia, T. (2010) · British Journal of Educational Technology · doi:10.1111/(issn)1467-8535 · Cited by 1,161 · see citing works
Application and theory gaps during the rise of artificial intelligence in education
Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100002 · Cited by 1,003 · see citing works
Revolutionizing education with AI: Exploring the transformative potential of ChatGPT
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13152 · Cited by 975 · cited 1× · see citing works
“Students enjoy personalized learning experiences through AI that respond to their individual needs and preferences 3 .”
BackgroundEmerging challenges in AI and the need for AI ethics education
Borenstein, J., & Howard, A. (2021) · AI and Ethics · doi:10.1007/s43681-020-00002-7 · Cited by 626 · see citing works
Artificial Intelligence for Student Assessment: A Systematic Review
González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021) · Applied Sciences · doi:10.3390/app11125467 · Cited by 503 · see citing works
Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots
Gill, S. S., Xu, M.-X., Patros, P., Wu, H.-M., Kaur, R., Kaur, K., Fuller, S., Singh, M., Arora, P., Parlikad, A., et al. (2023) · Internet Things Cyber Phys. Syst. · doi:10.1016/j.iotcps.2023.06.002 · Cited by 466 · see citing works
Yang, W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100061 · Cited by 440 · see citing works
Artificial intelligence in education
Robertson, M. (1976) · Nature · doi:10.1038/262435a0 · Cited by 310 · see citing works
Ethical principles for artificial intelligence in K-12 education
Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100131 · Cited by 288 · see citing works
Regan, P. M., & Jesse, J. (2019) · Ethics and Information Technology · doi:10.1007/s10676-018-9492-2 · Cited by 286 · see citing works
Lo Piano, S. (2020) · Humanities and Social Sciences Communications · doi:10.1057/s41599-020-0501-9 · Cited by 229 · see citing works
Toward personalized XAI: A case study in intelligent tutoring systems
Conati, C., Barral, O., Putnam, V., & Rieger, L. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103503 · Cited by 197 · see citing works
Alam, A. (2022) · International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) · doi:10.1109/icscds53736.2022.9760932 · Cited by 123 · see citing works
AI-Based Learning Style Prediction in Online Learning for Primary Education
Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022) · IEEE Access · doi:10.1109/access.2022.3160177 · Cited by 113 · see citing works
A pedagogy of data and Artificial intelligence for student subjectification.
Loftus, M., & Madden, M. G. (2020) · Teaching in Higher Education · doi:10.1080/13562517.2020.1748593 · Cited by 59 · see citing works
Algorithmic bias: should students pay the price?
Smith, H. (2020) · AI & SOCIETY · doi:10.1007/s00146-020-01054-3 · Cited by 52 · see citing works
Artificial Intelligence Ethics Guidelines for K-12 Education: A Review of the Global Landscape
Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2021) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-78270-2_4 · Cited by 48 · see citing works
Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI ChatbotsPreprint
Gill, S. S., Xu, M., Patros, P., Wu, H., Kaur, R., Kaur, K., Fuller, S., Singh, M., Arora, P., Parlikad, A. K., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2306.03823 · Cited by 37 · see citing works
Kılınç, S. (2023) · OpenMETU (Middle East Technical University) · doi:10.5281/zenodo.7857395 · Cited by 31 · see citing works
Kılınç, S. (2023) · OpenMETU (Middle East Technical University) · doi:10.5281/zenodo.7857396 · Cited by 29 · see citing works
Artificial intelligence in clinical practice: Implications for physiotherapy education
Rowe, M. (2019) · OpenPhysio Journal · doi:10.14426/art/528 · Cited by 14 · see citing works
Cyberphysical Systems in K–12 Education
Komninos, T., Paraskevas, M., Smyrnaiou, Z., & Serpanos, D. N. (2022) · Computer · doi:10.1109/mc.2022.3158165 · Cited by 5 · see citing works
Self-citationLIA: A Mathbot Assistant for First-grade Students
Moussiades, L., & Zografos, G. (2021) · European Journal of Engineering and Technology Research · doi:10.24018/ejers.2021.6.5.2519 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Rochegonde LD. New Laws of Robotics: Defending Human Expertise in the Age of AI. Politique Etrangere 2021;2:207-208.
- Grossman J, Lin Z, Sheng H, Wei JTZ, Williams JJ, Goel S. MathBot: Transforming online resources for learning math into conversational interactions. AAAI 2019.
- Rubel A, Castro C, Pham A. Algorithms and autonomy: the ethics of automated decision systems. Cambridge University Press 2021.
Cited by
Sorted by citations
Beyond Traditional Assessment: Exploring the Impact of Large Language Models on Grading Practices
Fagbohun, O., Iduwe, N. P., Abdullahi, M., Ifaturoti, A., & Nwanna, O. (2024) · Journal of Artificial Intelligence, Machine Learning and Data Science · doi:10.51219/jaimld/oluwole-fagbohun/19 · Cited by 68 · see citing works
Enhancing Educational Interactions: A Comprehensive Review of AI Chatbots in Learning Environments
Jain, V., Singh, I., Syed, M., Mondal, S., & Palai, D. R. (2024) · International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · doi:10.1109/icrito61523.2024.10522392 · Cited by 21 · see citing works
Eutsler, L., Rivera, B., Barnes, M., & Cummings, J. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2476589 · Cited by 16 · see citing works
Pitychoutis, K. M., & Rawahi, A. A. (2024) · Forum for Linguistic Studies · doi:10.30564/fls.v6i6.7297 · Cited by 12 · see citing works
AI in Professional Development for English Language Teachers
Charles, T. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9077-1.ch004 · Cited by 11 · see citing works
The role of integration of AI in Science Learning in Special Education Needs
Kotsari, K., & Smyrnaiou, Z. (2024) · International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion (DSAI) · doi:10.1145/3696593.3696639 · Cited by 4 · see citing works
Self-citationRevolutionizing Education with AI: Ethical Considerations in K-12 Settings
Gökçe, A. T. (2025) · Education and human development · doi:10.5772/intechopen.1012230 · Cited by 2 · see citing works
Smart Teaching: The Synergy of Multiple Intelligences and AI in EFL InstructionPreprint
Pitychoutis, K. M., & Rawahi, A. A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4975286 · Cited by 2 · see citing works
Intelligent Immersion: AI and VR Tools for Next-Generation Higher Education
Liakopoulos, K., & Liapakis, A. (2026) · AI in Education · doi:10.3390/aieduc2020013 · Cited by 1 · see citing works
Self-citationChasokela, D., & Hlongwane, J. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-5623-4.ch012 · Cited by 1 · see citing works
Emerging Trends and Big Ideas for the Future of Artificial Intelligence (AI) in Education
Venkateswaran, P. S., Kamatchi, S. D., & Ravikumar, V. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-1827-1.ch012 · Cited by 1 · see citing works
Comparison of Generative Artificial Intelligence Tools in the Assessment of Student Assignments
Novak, M., Andročec, D., & Picek, R. (2025) · International Conference on Software, Telecommunications and Computer Networks (SoftCOM) · doi:10.23919/softcom66362.2025.11197413 · Cited by 1 · see citing works
Kotsari, K., Smyrnaiou, Z., & Gena, Α. (2026) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-026-07485-z · Cited by 1 · see citing works
Self-citationIntroduction to Network Sensing Systems in Society 5.0
Kumar, A., Kanojiya, A. K., & Subitha, D. (2025) · doi:10.1002/9781394310890.ch1
Smyrnaiou, Z., & Kotsari, K. (2025) · Constructionism Conference Proceedings · doi:10.21240/constr/2025/8.x
Self-citationEthical Challenges in AI-Enabled Education: A PESTEL Analysis
Lü, Y., & Tian, J. (2025) · doi:10.1109/icaie64856.2025.11158638
Giray, L., Carreon, R. E., & Aragon, J. J. (2025) · International Conference on Artificial Intelligence and Teacher Education (ICAITE) · doi:10.1109/icaite68636.2025.11442543
Rosmayanti, V., Yuliana, B., Rusli, K., Ibrahim, M., & Hasnawati, H. (2026) · IGI Global eBooks · doi:10.4018/979-8-2600-0736-5.ch001
Mamangon, C. T., & Maya, B. J. (2026) · International Journal of Latest Technology in Engineering Management & Applied Science · doi:10.51583/ijltemas.2026.150500090
Algorithmic Jurisprudence and Humanistic Governance Architectures for AI in Pedagogical Ecologies
Alam, A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5213-8.ch021
AI-Enhanced Personalized Learning and Adaptive Curriculum Design in Digital Marketing Education
Eshniyozov, A., Aarthi, S., Ravikumar, R. N., Umarbek, J., Allakuliev, A., & Ataniyazov, J. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9893-8.ch005
Building Ethical AI Competencies in STEM Education
Velmurugan, R., Sudarvel, J., Bhuvaneswari, R., & Thirumalaisamy, R. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0383-1.ch013
- Authors
- Smyrnaiou, Z., Liapakis, A., & Bougia, A.
- Affiliations
- National and Kapodistrian University of Athens (GR)
- Computer Technology Institute and Press “DIOPHANTUS” (GR)
- Corresponding author
- Liapakis, Anastasios
- Venue
- Journal of Artificial Intelligence, Machine Learning and Data Science
- Publisher
- United Research Forum
- Published
- 2023-10-12
- Volume
- 1
- Issue
- 4
- Pages
- 119-124
- ISSN
- 2583-9888 (ISSN-L)
- OpenAlex
- W4387569772
- Cited by
- 22
- References
- 27
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 5
- FWCI
- 5.16
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Artificial Intelligence Machine Learning and Data Science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence in education, AI ethics, academic integrity, cheating, K-12 education, AI tools, responsible AI use, student engagement, plagiarism detection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
